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Worldviews on Evidence-Based Nursing is a bimonthly peer-reviewed nursing journal covering research on nursing practice. It is published by Wiley and was established in 1993 as The Online Journal of Knowledge Synthesis for Nursing. The founding editors-in-chief were Donna Knauth and Jacqueline Fawcett.
One method of research for evidence-based practice in nursing is 'qualitative research': The word implies an entity and meanings that are not experimentally examined or measured in terms of quantity, amount, frequency, or intensity. With qualitative research, researchers learn about patient experiences through discussions and interviews.
For example, a pain-relief drug is tested on 1500 human subjects, and no adverse event is recorded. From the rule of three, it can be concluded with 95% confidence that fewer than 1 person in 500 (or 3/1500) will experience an adverse event. By symmetry, for only successes, the 95% confidence interval is [1−3/ n,1].
The model was developed by Dr. Kathleen Stevens at the Academic Center for Evidence-Based Practice located at the University of Texas Health Science Center at San Antonio. [3] The model has been represented in many nursing textbooks , used as part of an intervention to increase EBP competencies, and as a framework for instruments measuring EBP ...
[1] [2] The confidence level, degree of confidence or confidence coefficient represents the long-run proportion of CIs (at the given confidence level) that theoretically contain the true value of the parameter; this is tantamount to the nominal coverage probability. For example, out of all intervals computed at the 95% level, 95% of them should ...
The confidence interval summarizes a range of likely values of the underlying population effect. Proponents of estimation see reporting a P value as an unhelpful distraction from the important business of reporting an effect size with its confidence intervals, [ 7 ] and believe that estimation should replace significance testing for data analysis.
A common way to do this is to state the binomial proportion confidence interval, often calculated using a Wilson score interval. Confidence intervals for sensitivity and specificity can be calculated, giving the range of values within which the correct value lies at a given confidence level (e.g., 95%). [26]
A confidence interval states there is a 100γ% confidence that the parameter of interest is within a lower and upper bound. A common misconception of confidence intervals is 100γ% of the data set fits within or above/below the bounds, this is referred to as a tolerance interval, which is discussed below.